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Single-Cell RNA Sequencing Identifies Stem-Like Subpopulations and Their Gene Signature in Lung Adenocarcinoma Progression

ABSTRACT: Lung adenocarcinoma (LUAD) exhibits substantial intra-tumor heterogeneity (ITH), contributing to disease progression and therapeutic challenges. This study utilized single-cell RNA sequencing (scRNA-seq) to profile cells from stage I and III LUAD tumors and matched normal tissues, aiming to delineate malignant cell states and identify tumor-propagating subpopulations. Unsupervised clustering revealed eight major cell lineages, with epithelial cells dominating in tumors and a shift toward immunosuppressive niches in advanced stages, including elevated T cell exhaustion and pro-angiogenic macrophages. Malignant cells formed 11 subclusters, with stage III tumors enriched for invasive and immunosuppressive states. Pseudotime analysis suggested evolutionary trajectories from alveolar-like to squamous and stress-responsive lineages. Using CytoTRACE to infer stemness without predefined markers, we identified sub-cancer stem cells (sub-CSCs) predominantly in stage III, characterized by high transcriptional diversity and a core signature involving cytoskeleton motility, immune modulation, metabolic reprogramming, and protein homeostasis. A four-gene panel demonstrated strong prognostic value in independent cohorts. These findings provide insights into stemness-driven progression in LUAD and nominate potential targets for addressing heterogeneity.

ORGANISM(S): Homo sapiens

PROVIDER: GSE333596 | GEO | 2026/07/31

REPOSITORIES: GEO

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Project description:Background: Image-based screening improves the detection of early-stage lung adenocarcinoma (LUAD)but also highlights the issue of high false-positive diagnoses, which puts patients at a risk of unnecessary over-treatment. Therefore, more precise discrimination criteria are required to ensure that patients with early-stage LUAD receive appropriate treatments. Methods: we integrated 158 early-stage LUAD cases from 2 independent cohorts, including 30 matched resected specimens with complete radiological and pathological information, and 128 retrospective pathological pair-samples with partial follow-up data. This integration allowed us to conduct a correlation analysis between clinical phenotype and transcriptome landscape. Immunohistochemistry was performed using tissue microarrays to examine the expression of phospholipid phosphatase 2 (PLPP2) and lipid-raft markers. Lipidomics analysis was used to determine the changes of lipid components in PLPP2-overexpressed cells. To assess the effects of PLPP2 on the malignant phenotypes of LUAD cells, we conducted mice tumor-bearing experiments and in vitro cellular experiments by knocking down PLPP2 and inhibiting lipid raft synthesis with MβCD, respectively. Results: Bioinformatics analysis indicated that the co-occurrence of lipid raft formation and rapid cell proliferation might exhibit synergistic effects in driving oncogenesis from lung preneoplasia to adenocarcinoma. The enhanced activation of the cell cycle promoted the transition from non-invasive to invasive status in early-stage LUAD, which was related to an increase in lipid rafts within LUAD cells. PLPP2 participated in lipid raft formation by altering the component contents of lipid rafts, such as esters, sphingomyelin, and sphingosine. Furthermore, elevated PLPP2 levels were identified as an independent prognostic risk factor for LUAD patients. Further results from in vivo and in vitro experiments confirmed that PLPP2 could induce excessive cell proliferation by enhancing lipid raft formation in LUAD cells. Conclusions: Our study has revealed the characteristics of gene expression profiles in early-stage LUAD patients with the different radiological and pathological subtypes, as well as deciphered transcriptomic evolution trajectory from preneoplasia to invasive LUAD. Furthermore, it suggests that PLPP2-mediated lipid raft synthesis may be a significant biological event in the initiation of early-stage LUAD, offering a potential target for more precise diagnosis and therapy in clinical settings.

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Single-Cell RNA Sequencing Identifies Stem-Like Subpopulations and Their Gene Signature in Lung Adenocarcinoma Progression

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